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Engine and aftertreatment solutions have been identified to meet the upcoming ultra-low NOX regulations on heavy duty vehicles in the United States and Europe. These standards will require changes to current conventional aftertreatment systems for dealing with low exhaust temperature scenarios while increasing the useful life of the engine and aftertreatment system. Previous studies have shown feasibility of meeting the US EPA and California Air Resource Board (CARB) requirements. This work includes a 15L diesel engine equipped with cylinder deactivation (CDA) and an aftertreatment system that was fully DAAAC aged to 800,000 miles. The aftertreatment system includes an e-heater (electric heater), light-off Selective Catalytic Reduction (LO-SCR) followed by a primary aftertreatment system containing a DPF and SCR.

In response to global climate change, there is a widespread push to reduce carbon emissions in the transportation sector. For the difficult to decarbonize heavy-duty (HD) vehicle sector, lower carbon intensity fuels can offer a low-cost, near-term solution for CO2 reduction. The use of natural gas can provide such an alternative for HD vehicles while the increasing availability of renewable natural gas affords the opportunity for much deeper reductions in net-CO2 emissions. With this in consideration, the US National Renewable Energy Laboratory launched the Natural Gas Vehicle Research and Development Project to stimulate advancements in technology and availability of natural gas vehicles. As part of this program, Southwest Research Institute developed a hybrid-electric medium-HD vehicle (class 6) to demonstrate a substantial CO2 reduction over the baseline diesel vehicle and ultra-low NOx emissions.

A model-based torque control strategy which is simple and easily adaptable to various types of engines is developed in this paper. A torque model is derived from constant-volume combustion model, and applications of the model to engine torque control problem are also discussed. As examples, the torque model is calibrated with experimental data collected from two different engines, and simulation and experimental results from the torque control strategy are presented as well.

The paper presents a robust adaptive control technique for precise regulation of a port fuel injection + direct injection (PFI+DI) system, a dual fuel injection configuration adopted in modern gasoline engines to boost performance, fuel efficiency, and emission reduction. Addressing parametric uncertainties on the actuators, inherent in complex fuel injection systems, the proposed approach utilizes an indirect model reference adaptive control scheme. To accommodate the increased control complexity in PFI+DI and the presence of additional uncertainties, a nonlinear plant model is employed, incorporating dynamics of the exhaust burned gas fraction. The primary objective is to optimize engine performance while minimizing fuel consumption and emissions in the presence of uncertainties. Stability and tracking performance of the adaptive controller are evaluated to ensure safe and reliable system operation under various conditions.

When an SI engine is equipped with individual cylinder pressure transducers, combustion timing of each cylinder can be precisely controlled by adjusting spark timing in real-time. In this paper, a novel method based on principal component analysis (PCA) is introduced to control the combustion timing with a significantly less computational burden than a conventional method.

In this study, engine-out gaseous emissions are reviewed using the Fourier Transform Infrared (FTIR) spectroscopy measurement of methanol diesel dual fuel combustion experiments performed in a heavy-duty diesel engine. Comparison to the baseline diesel-only condition shows that methanol-diesel dual fuel combustion leads to higher regulated carbon monoxide (CO) emissions and unburned hydrocarbons (UHC). However, NOX emissions were reduced effectively with increasing methanol substitution rate (MSR). Under dual-fuel operation with methanol, emissions of nitrogen oxides (NOX), including nitric oxide (NO), nitrogen dioxide (NO2), and nitrous oxide (N2O), indicate the potential to reduce the burden of NOX on diesel after-treatment devices such as selective catalytic reduction (SCR).

Pouch cells are increasingly popular form factors for the construction of energy storage systems in electric vehicles of all classes. Knowledge of the stress generated by these higher capacity pouch cells is critical to properly design battery modules and packs for both normal and abnormal operation. Existing literature predominantly offers data on smaller pouch cells with capacities of less than 10 Ah, leaving a gap in our understanding of the behavior of these larger cells. This experimental study aimed to bridge this knowledge gap by measuring loads and stresses in constrained 65 Ah pouch cells under both cycling and abuse conditions. To capture the desired responses, a load cell was located within a robust fixture to measure cell stress in real time after the application of a preload of approximately 30 kilograms or 294 N, equivalent to a pressure of 0.063 bar, with a fixed displacement.

Range anxiety in current battery electric vehicles is a challenging problem, especially for commercial vehicles with heavy payloads. Therefore, the development of electrified propulsion systems with multiple power sources, such as fuel cells, is an active area of research. Optimal speed planning and energy management, referred to as eco-driving, can substantially reduce the energy consumption of commercial vehicles, regardless of the powertrain architecture. Eco-driving controllers can leverage look-ahead route information such as road grade, speed limits, and signalized intersections to perform velocity profile smoothing, resulting in reduced energy consumption. This study presents a comprehensive analysis of the performance of an eco-driving controller for fuel cell electric trucks in a real-world scenario, considering a route from a distribution center to the associated supermarket.

In electric vehicle applications, the majority of the traction motors can be categorized as Permanent Magnet (PM) motors due to their outstanding performance. As indicated in the name, there are strong permanent magnets used inside the rotor of the motor, which interacts with the stator and causes strong magnetic pulling force during the assembly process. How to estimate this magnetic pulling force can be critical for manufacturing safety and efficiency. In this paper, a full 3D magnetostatic model has been proposed to calculate the baseline force using a dummy non-slotted cylinder stator and a simplified rotor for less meshing elements. Then, the full 360 deg model is simplified to a half-pole model based on motor symmetry to save the simulation time from 2 days to 2 hours. A rotor position sweep was conducted to find the maximum pulling force position. The result shows that the max pulling force happens when the rotor is 1% overlapping with the stator core.

As part of the U.S. Environmental Protection Agency’s (EPA’s) continuing assessment of advanced light-duty automotive technologies in support of regulatory and compliance programs, a development project was started to study various test methods to benchmark Electric Drive Units (EDUs) consisting of an electric motor, inverter and a speed-reduction gearset. Several test methods were identified for consideration, including both in-vehicle testing of the complete EDU and stand-alone testing of the EDU and its subcomponents after removal from the vehicle. In all test methods explored, sweeps of speed and torque test points were conducted while collecting key EDU data required to determine efficiency, including motor torque and speed, direct current (DC) battery voltage and current into the inverter, and three-phase alternating current (AC) phase voltages and currents out of the inverter and into the electric motor.

A linear parameter-varying model predictive control (LPVMPC) is proposed to enhance the longitudinal vehicle speed control of a gas-engine vehicle, with potential application in autonomous vehicles. To achieve this objective, an advanced vehicle dynamic model and a sophisticated fuel consumption model are derived, forming a control-oriented model for the proposed control system. The vehicle dynamic model accurately captures the motions of the tires and the vehicle body. The fuel consumption model incorporates new powertrain modes such as automatic engine stop/start, active fuel management, and deceleration fuel cut-off, etc. The performance of the proposed LPV-MPC is evaluated by comparing it to a PID controller. Both simulation tests and vehicle-in-the-loop tests demonstrate the superior performance of the proposed controller. The results indicate that the LPV-MPC provides improved longitudinal vehicle speed control and reduced fuel consumption.

The widely accepted best practice for spark-ignition combustion is the four-valve pent-roof chamber using a central sparkplug and incorporating tumble flow during the intake event. The bulk tumble flow readily breaks up during the compression stroke to fine-scale turbulent kinetic energy desired for rapid, robust combustion. The natural gas engines used in medium- and heavy-truck applications would benefit from a similar, high-tumble pent-roof combustion chamber. However, these engines are invariably derived from their higher-volume diesel counterparts, and the production volumes are insufficient to justify the amount of modification required to incorporate a pent-roof system. The objective of this multi-dimensional computational study was to develop a combustion chamber addressing the objectives of a pent-roof chamber while maintaining the flat firedeck and vertical valve orientation of the diesel engine.

The proposed Euro 7 regulation includes On Board Monitoring, or OBM, to continuously monitor vehicles for emission exceedances. OBM relies on feedback from existing or additional sensors to identify high emitting vehicles, which poses many challenges. Currently, sensors are not commercially available for all emissions constituents, and the accuracy of available sensors is not capable enough for in use compliance determination. On board emissions models do not offer enough fidelity to determine in use compliance and require new complex model innovation development which will be extremely complicated to implement on board the vehicle. The stack up of multi-component deterioration leading to an emissions exceedance is infeasible to detect using available sensors and models.

Crankshaft bearings function to maintain the lubrication oil films needed to support crankshaft journals in hydrodynamic regime of rotation. Discontinuous oil films will cause the journal-bearing couple to be in a mixed or boundary lubrication condition, or even a bearing seizure or a spun bearing. This condition may further force the crankshaft to break and an engine shutdown. Spun bearings have been identified to be one of the top reasons in field returned engines. Excessive investigations have found large, embedded hard debris particles on the bearings are inevitably the culprit of destroying continuity of the oil films. Those particles, in particular the suspicious steel residues, in the sizes of hundreds of micrometers, are large enough to cause oil film to break, but rather fine and challenging for materials engineers to characterize their metallurgical features. This article presents the methodology and steps of debris analyses on bearings at different stages of engine build.

In this paper, we present a novel algorithm designed to accurately trigger the engine coolant flow at the optimal moment, thereby safeguarding gas-engines from catastrophic failures such as engine boil. To achieve this objective, we derive models for crucial temperatures within a gas-engine, including the engine combustion wall temperature, engine coolant-out temperature, engine block temperature, and engine oil temperature. To overcome the challenge of measuring hard-to-measure signals such as engine combustion gas temperature, we propose the use of new intermediate parameters. Our approach utilizes a lumped parameter concept with a mean-value approach, enabling precise temperature prediction and rapid simulation. The proposed engine thermal model is capable of estimating temperatures under various conditions, including steady-state or transient engine performance, without the need for extra sensors.

To meet the stringent NOx and particulate emissions requirements of Euro 6 and China 6 standard, Selective Catalyst Reduction (SCR) catalyst integrated with wall flow particulate filter (SCR-DPF) has been found to be an effective solution for the exhaust aftertreatment systems of diesel engines. NOx is reduced by ammonia generated from urea injection while the filter effectively traps and burns the particulate matter periodically in a process called regeneration. The engine control unit (ECU) effectively manages urea injection quantity, timing and soot burning frequency for the stable functioning of the SCR-DPF without impacting drivability. To control the NOx reduction and particulate regeneration process, the control unit uses lookup tables generated from extensive hardware testing to get the current soot load and NOx slip information of SCR-DPF as a function of main exhaust state variables.

Electric vehicles (EV) present distinctive challenges compared to ICE (Internal Combustion Engine) powered counterparts. Cabin heating and air-conditioning stand out among them, especially cabin heating in cold weather, owing to its outsized effect on drivable range of the vehicle. Efficient management of the cabin thermal system has the potential to improve vehicle range without compromising passenger comfort. A method to improve cabin thermal system regulation by effectively leveraging the solar load on the vehicle is proposed in this work. The methodology utilizes connectivity and mapping data to predict the solar load over a future time horizon. Typically, the solar load is treated as an unmeasured external disturbance which is compensated with control. It can however be treated as an estimated quantity with potential to enable predictive control. The solar load prediction, coupled with a passenger thermal comfort model, enables preemptive thermal system control over a route.

As GHG and fuel economy regulations of light-duty vehicles have become more stringent, advanced emissions reduction technology has extensively penetrated the US light-duty vehicle fleet. This new technology includes not only advanced conventional engines and transmissions, but also greater adoption of electrified powertrains. In 2022, electrified vehicles – including mild hybrids, strong hybrids, plug-ins, and battery electric vehicles – made up nearly 17% of the US fleet and are on track to further increase their proportion in subsequent years. The Environmental Protection Agency (EPA) has previously used its Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) full vehicle simulation tool to evaluate the greenhouse gas (GHG) emissions of light-duty vehicles. ALPHA contains a library of benchmarked powertrain components that can be matched to specific vehicles to explore GHG emissions performance.

Cast austenitic stainless steels, such as 1.4837Nb, are widely used for turbo housing and exhaust manifolds which are subjected to elevated temperatures. Due to assembly constraints, geometry limitation, and particularly high temperatures, thermomechanical fatigue (TMF) issue is commonly seen in the service of those components. Therefore, it is critical to understand the TMF behavior of the cast steels. In the present study, a series of fatigue tests including isothermal low cycle fatigue tests at elevated temperatures up to 1100°C, in-phase and out-of-phase TMF tests in the temperature ranges 100-800°C and 100-1000°C have been conducted. Both creep and oxidation are active in these conditions, and their contributions to the damage of the steel are discussed.

This paper details testing for torque converter clutch (TCC) characterization during steady state and dynamic operation under controlled slip conditions on a dynamometer setup. The subject torque converter under test is a twin plate clutch with a dual stage turbine damper without a centrifugal pendulum absorber. An overview is provided of the dynamometer setup, hydraulic system and control techniques for regulating the apply pressure to the torque converter and clutch. To quantify the performance of the clutch in terms of control stability, pressure to torque relationship and the dynamic behavior during apply and release, a matrix of oil temperatures, output speeds, input torques, and clutch apply pressures were imposed upon the torque converter.